{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0ace62ba",
   "metadata": {},
   "source": [
    "# 贝叶斯判别准则族"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9973877",
   "metadata": {},
   "source": [
    "## 基本原理"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c63d0020",
   "metadata": {},
   "source": [
    "统计学似然比准则\n",
    "$$\n",
    "    \\left\\{\n",
    "    \\begin{array}{ll}\n",
    "    x \\in G_1 &, \\frac{f_1(x)}{f_2(x)} \\ge \\frac{L(1|2)p_{2}}{L(2|1)p_{1}} \\\\\n",
    "    x \\in G_2 &, \\frac{f_1(x)}{f_2(x)} < \\frac{L(1|2)p_{2}}{L(2|1)p_{1}} \n",
    "    \\end{array}\n",
    "    \\right. \n",
    "$$\n",
    "\\* 其中$p_{1}$、$p_{2}$是两个分布的先验概率，一般可以使用样本数量进行近似，即\n",
    "$$\n",
    "    \\left\\{\n",
    "    \\begin{array}\n",
    "    p_{1} = \\frac{n_{1}}{n_{1}+n_{2}} \\\\\n",
    "    p_{2} = \\frac{n_{2}}{n_{1}+n_{2}}\n",
    "    \\end{array}\n",
    "    \\right.\n",
    "$$\n",
    "\\* 而$L(1|2)$、$L(2|1)$是分类的损失，一般情况下选取为1\n",
    "\n",
    "一般我们认为总体服从多元$x \\in R^{p}$正态分布，意即\n",
    "$$\n",
    "    f_{i}(x) = (2\\pi)^{-\\frac{p}{2}}|\\Sigma^{-\\frac{1}{2}}|exp\\{-\\frac{1}{2}{(x-\\mu_{i})}^T\\Sigma^{-1}(x-\\mu_{i})\\}\n",
    "$$\n",
    "设总体$X_i ~ N_p(\\mu_i,\\Sigma_i), i=1,2$\n",
    "那么对于两个整体$G_1,G_2$而言，\n",
    "$$\n",
    "    \\left\\{\n",
    "    \\begin{array}{ll}\n",
    "    R_1 = \\{x: W(x) \\ge \\beta\\} \\\\\n",
    "    R_2 = \\{x: W(x) < \\beta\\}\n",
    "    \\end{array}\n",
    "    \\right.\n",
    "$$\n",
    "1. 两整体协方差矩阵相同$\\Sigma_1=\\Sigma_2=\\Sigma$\n",
    "$$\n",
    "     W(x)=[x-\\frac{1}{2}(\\mu_1+\\mu_2)]^T\\Sigma^{-1}(\\mu_1-\\mu_2) \\\\\n",
    "     \\beta = ln\\frac{L(1|2)\\cdot p_2}{L(2|1)\\cdot p_1}\n",
    "$$\n",
    "2. 两整体协方差矩阵不相同$\\Sigma_1 \\ne \\Sigma_2$\n",
    "$$\n",
    "    W(x)=-\\frac{1}{2}x^T(\\Sigma_{1}^{-1}-\\Sigma_{2}^{-1})x+(\\mu_1^T\\Sigma_{1}^{-1}-\\mu_2^T\\Sigma_{2}^{-1})x \\\\\n",
    "    \\beta = ln\\frac{L(1|2)\\cdot p_2}{L(2|1)\\cdot p_1} + \\frac{1}{2}ln\\frac{|\\Sigma_1|}{|\\Sigma_2|}+\\frac{1}{2}(\\mu_1^T\\Sigma_{1}^{-1}\\mu_1 - \\mu_2^T\\Sigma_{2}^{-1}\\mu_2)\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3277a1ec",
   "metadata": {},
   "source": [
    "## Mahalonobis Distance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fbf4409",
   "metadata": {},
   "source": [
    "## 定义\n",
    "$$\n",
    "    d^{2}(\\vec x, G) = (\\vec x - \\mu)^{T}\\Sigma^{-1} (\\vec x - \\mu)\n",
    "$$\n",
    "\\* 其中，$\\Sigma$是协方差矩阵，$\\mu$是分布的期望\n",
    "\n",
    "## 作用\n",
    "1. 区分离群值\n",
    "2. 基于线性相关属性进行准确分类\n",
    "3. 本质上是对数据进行标准化预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b49835fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>depth</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>61.5</td>\n",
       "      <td>326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>59.8</td>\n",
       "      <td>326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>56.9</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>62.4</td>\n",
       "      <td>334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>63.3</td>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   carat  depth  price\n",
       "0   0.23   61.5    326\n",
       "1   0.21   59.8    326\n",
       "2   0.23   56.9    327\n",
       "3   0.29   62.4    334\n",
       "4   0.31   63.3    335"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import scipy as sp\n",
    "import numpy as np\n",
    "\n",
    "filepath = 'https://raw.githubusercontent.com/selva86/datasets/master/diamonds.csv'\n",
    "df = pd.read_csv(filepath).iloc[:, [0,4,6]]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ec0e85d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>depth</th>\n",
       "      <th>price</th>\n",
       "      <th>mahala</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>61.5</td>\n",
       "      <td>326</td>\n",
       "      <td>1.709860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>59.8</td>\n",
       "      <td>326</td>\n",
       "      <td>3.540097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>56.9</td>\n",
       "      <td>327</td>\n",
       "      <td>12.715021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>62.4</td>\n",
       "      <td>334</td>\n",
       "      <td>1.454469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>63.3</td>\n",
       "      <td>335</td>\n",
       "      <td>2.347239</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   carat  depth  price     mahala\n",
       "0   0.23   61.5    326   1.709860\n",
       "1   0.21   59.8    326   3.540097\n",
       "2   0.23   56.9    327  12.715021\n",
       "3   0.29   62.4    334   1.454469\n",
       "4   0.31   63.3    335   2.347239"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def mahalanobis(x=None, data=None, cov=None):\n",
    "    \"\"\"Compute the Mahalanobis Distance between each row of x and the data  \n",
    "    x    : vector or matrix of data with, say, p columns.\n",
    "    data : ndarray of the distribution from which Mahalanobis distance of each observation of x is to be computed.\n",
    "    cov  : covariance matrix (p x p) of the distribution. If None, will be computed from data.\n",
    "    \"\"\"\n",
    "    x_minus_mu = x - np.mean(data)\n",
    "    if not cov:\n",
    "        cov = np.cov(data.values.T)\n",
    "    inv_covmat = np.linalg.inv(cov)\n",
    "    left_term = np.dot(x_minus_mu, inv_covmat)\n",
    "    mahal = np.dot(left_term, x_minus_mu.T)\n",
    "    return np.diagonal(mahal)\n",
    "\n",
    "df_x = df[['carat', 'depth', 'price']].head(500)\n",
    "data = df[['carat', 'depth', 'price']]\n",
    "df_x['mahala'] = mahalanobis(x=df_x, data=data)\n",
    "df_x.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bcde4bf",
   "metadata": {},
   "source": [
    "# 多元异常值检测"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49fdfe1c",
   "metadata": {},
   "source": [
    "## 置信区间假设检验\n",
    "假设检验的置信区间$\\alpha=0.01$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a55d3df8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>depth</th>\n",
       "      <th>price</th>\n",
       "      <th>mahala</th>\n",
       "      <th>p_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>56.9</td>\n",
       "      <td>327</td>\n",
       "      <td>12.715021</td>\n",
       "      <td>0.001734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>0.86</td>\n",
       "      <td>55.1</td>\n",
       "      <td>2757</td>\n",
       "      <td>23.909643</td>\n",
       "      <td>0.000006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.96</td>\n",
       "      <td>66.3</td>\n",
       "      <td>2759</td>\n",
       "      <td>11.781773</td>\n",
       "      <td>0.002765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>1.17</td>\n",
       "      <td>60.2</td>\n",
       "      <td>2774</td>\n",
       "      <td>9.279459</td>\n",
       "      <td>0.009660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>0.98</td>\n",
       "      <td>67.9</td>\n",
       "      <td>2777</td>\n",
       "      <td>20.086616</td>\n",
       "      <td>0.000043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>0.70</td>\n",
       "      <td>57.2</td>\n",
       "      <td>2782</td>\n",
       "      <td>10.405659</td>\n",
       "      <td>0.005501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>0.84</td>\n",
       "      <td>55.1</td>\n",
       "      <td>2782</td>\n",
       "      <td>23.548379</td>\n",
       "      <td>0.000008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>1.05</td>\n",
       "      <td>65.8</td>\n",
       "      <td>2789</td>\n",
       "      <td>11.237146</td>\n",
       "      <td>0.003630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284</th>\n",
       "      <td>1.00</td>\n",
       "      <td>58.2</td>\n",
       "      <td>2795</td>\n",
       "      <td>10.349019</td>\n",
       "      <td>0.005659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>1.01</td>\n",
       "      <td>67.4</td>\n",
       "      <td>2797</td>\n",
       "      <td>17.716144</td>\n",
       "      <td>0.000142</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     carat  depth  price     mahala   p_value\n",
       "2     0.23   56.9    327  12.715021  0.001734\n",
       "91    0.86   55.1   2757  23.909643  0.000006\n",
       "97    0.96   66.3   2759  11.781773  0.002765\n",
       "172   1.17   60.2   2774   9.279459  0.009660\n",
       "204   0.98   67.9   2777  20.086616  0.000043\n",
       "221   0.70   57.2   2782  10.405659  0.005501\n",
       "227   0.84   55.1   2782  23.548379  0.000008\n",
       "255   1.05   65.8   2789  11.237146  0.003630\n",
       "284   1.00   58.2   2795  10.349019  0.005659\n",
       "298   1.01   67.4   2797  17.716144  0.000142"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import chi2\n",
    "\n",
    "alpha = chi2.ppf((1-0.01),df=2)\n",
    "df_trimmed_1 = df_x[(df_x['mahala']>alpha)]\n",
    "df_trimmed_1.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d3eda4a",
   "metadata": {},
   "source": [
    "## 显著性水平假设检验\n",
    "接下来使用显著性水平$p$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "01785c50",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>carat</th>\n",
       "      <th>depth</th>\n",
       "      <th>price</th>\n",
       "      <th>mahala</th>\n",
       "      <th>p_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>56.9</td>\n",
       "      <td>327</td>\n",
       "      <td>12.715021</td>\n",
       "      <td>0.001734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>0.86</td>\n",
       "      <td>55.1</td>\n",
       "      <td>2757</td>\n",
       "      <td>23.909643</td>\n",
       "      <td>0.000006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.96</td>\n",
       "      <td>66.3</td>\n",
       "      <td>2759</td>\n",
       "      <td>11.781773</td>\n",
       "      <td>0.002765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>1.17</td>\n",
       "      <td>60.2</td>\n",
       "      <td>2774</td>\n",
       "      <td>9.279459</td>\n",
       "      <td>0.009660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>0.98</td>\n",
       "      <td>67.9</td>\n",
       "      <td>2777</td>\n",
       "      <td>20.086616</td>\n",
       "      <td>0.000043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>0.70</td>\n",
       "      <td>57.2</td>\n",
       "      <td>2782</td>\n",
       "      <td>10.405659</td>\n",
       "      <td>0.005501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>0.84</td>\n",
       "      <td>55.1</td>\n",
       "      <td>2782</td>\n",
       "      <td>23.548379</td>\n",
       "      <td>0.000008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>1.05</td>\n",
       "      <td>65.8</td>\n",
       "      <td>2789</td>\n",
       "      <td>11.237146</td>\n",
       "      <td>0.003630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284</th>\n",
       "      <td>1.00</td>\n",
       "      <td>58.2</td>\n",
       "      <td>2795</td>\n",
       "      <td>10.349019</td>\n",
       "      <td>0.005659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>1.01</td>\n",
       "      <td>67.4</td>\n",
       "      <td>2797</td>\n",
       "      <td>17.716144</td>\n",
       "      <td>0.000142</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     carat  depth  price     mahala   p_value\n",
       "2     0.23   56.9    327  12.715021  0.001734\n",
       "91    0.86   55.1   2757  23.909643  0.000006\n",
       "97    0.96   66.3   2759  11.781773  0.002765\n",
       "172   1.17   60.2   2774   9.279459  0.009660\n",
       "204   0.98   67.9   2777  20.086616  0.000043\n",
       "221   0.70   57.2   2782  10.405659  0.005501\n",
       "227   0.84   55.1   2782  23.548379  0.000008\n",
       "255   1.05   65.8   2789  11.237146  0.003630\n",
       "284   1.00   58.2   2795  10.349019  0.005659\n",
       "298   1.01   67.4   2797  17.716144  0.000142"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_x['p_value'] = 1 - chi2.cdf(df_x['mahala'],df=2)\n",
    "df_x.loc[df_x.p_value < 0.01].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "454e5f8b",
   "metadata": {},
   "source": [
    "# 二分类问题\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "54c9b37f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cl.thickness</th>\n",
       "      <th>Cell.size</th>\n",
       "      <th>Marg.adhesion</th>\n",
       "      <th>Epith.c.size</th>\n",
       "      <th>Bare.nuclei</th>\n",
       "      <th>Bl.cromatin</th>\n",
       "      <th>Normal.nucleoli</th>\n",
       "      <th>Mitoses</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Cl.thickness  Cell.size  Marg.adhesion  Epith.c.size  Bare.nuclei  \\\n",
       "0             5          1              1             2          1.0   \n",
       "1             5          4              5             7         10.0   \n",
       "2             3          1              1             2          2.0   \n",
       "3             6          8              1             3          4.0   \n",
       "4             4          1              3             2          1.0   \n",
       "\n",
       "   Bl.cromatin  Normal.nucleoli  Mitoses  Class  \n",
       "0            3                1        1      0  \n",
       "1            3                2        1      0  \n",
       "2            3                1        1      0  \n",
       "3            3                7        1      0  \n",
       "4            3                1        1      0  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/selva86/datasets/master/BreastCancer.csv', \n",
    "                 usecols=['Cl.thickness', 'Cell.size', 'Marg.adhesion', \n",
    "                          'Epith.c.size', 'Bare.nuclei', 'Bl.cromatin', 'Normal.nucleoli', \n",
    "                          'Mitoses', 'Class'])\n",
    "\n",
    "df.dropna(inplace=True)  # drop missing values.\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "f4c252af",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "x_train, x_test, y_train, y_test = train_test_split(df.drop('Class',axis=1),\n",
    "                                                    df['Class'],test_size=0.2,\n",
    "                                                    random_state=100)\n",
    "x_train_pos = x_train.loc[y_train == 1, :]\n",
    "x_test_pos = x_test.loc[y_test == 1, :]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47c4e09b",
   "metadata": {},
   "source": [
    "## 构建分类器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "be5b06c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "class MahalanobisBinaryClassifier():\n",
    "    def __init__(self, x_train, y_train):\n",
    "        self.x_train_pos = x_train.loc[y_train==1,:]\n",
    "        self.x_train_neg = x_train.loc[y_train==0,:]\n",
    "        \n",
    "    def predict_proba(self, x_test):\n",
    "        pos_neg_dists = [(pos,neg) \n",
    "                         for pos,neg in zip(mahalanobis(x_test, self.x_train_pos),\n",
    "                                           mahalanobis(x_test, self.x_train_neg))]\n",
    "        return np.array([(1-neg/(pos+neg),1-pos/(pos+neg)) for pos,neg in pos_neg_dists])\n",
    "    \n",
    "    def predict(self, x_test):\n",
    "        return np.array([np.argmax(row) for row in self.predict_proba(x_test)])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "27241396",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>prediction</th>\n",
       "      <th>actual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   prediction  actual\n",
       "0           0       0\n",
       "1           1       1\n",
       "2           0       0\n",
       "3           0       0\n",
       "4           0       0\n",
       "5           0       0\n",
       "6           0       0\n",
       "7           1       0\n",
       "8           1       0\n",
       "9           1       1"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mahal_clf = MahalanobisBinaryClassifier(x_train, y_train)\n",
    "pred_probas = mahal_clf.predict_proba(x_test)\n",
    "pred_res = mahal_clf.predict(x_test)\n",
    "\n",
    "pred_act = pd.DataFrame([(pred, act) for pred,act in zip(pred_res, y_test)],\n",
    "                        columns=['prediction','actual'])\n",
    "pred_act.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43f38caa",
   "metadata": {},
   "source": [
    "## 分类器检测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "f9bf07b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUROC:  0.9912529550827424\n",
      "\n",
      "Confusion Matrix: \n",
      " [[76 14]\n",
      " [ 0 47]]\n",
      "\n",
      "Accuracy Score:  0.8978102189781022\n",
      "\n",
      "Classification Report: \n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.84      0.92        90\n",
      "           1       0.77      1.00      0.87        47\n",
      "\n",
      "    accuracy                           0.90       137\n",
      "   macro avg       0.89      0.92      0.89       137\n",
      "weighted avg       0.92      0.90      0.90       137\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "truth = pred_act.loc[:,'actual']\n",
    "pred = pred_act.loc[:,'prediction']\n",
    "scores = np.array(pred_probas)[:,1]\n",
    "print('AUROC: ', roc_auc_score(truth, scores))\n",
    "print('\\nConfusion Matrix: \\n', confusion_matrix(truth, pred))\n",
    "print('\\nAccuracy Score: ', accuracy_score(truth, pred))\n",
    "print('\\nClassification Report: \\n', classification_report(truth, pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe8678be",
   "metadata": {},
   "source": [
    "# 多分类问题"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcfa8bd9",
   "metadata": {},
   "source": [
    "## 构建分类器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0086b321",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "56a6cbb0",
   "metadata": {},
   "source": [
    "# 卡方分布$\\chi^2$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e04da38",
   "metadata": {},
   "source": [
    "## ppf函数\n",
    "1. ppf函数是cdf函数的逆函数\n",
    "2. 通过给定cdf一个x值，能够求出该x值出现的概率是多少\n",
    "    1. 如果是p置信区间进行估计，查看第一类错误区间是否在p置信区间内，若在则接受备择假设\n",
    "    2. 如果是$\\alpha$置信度进行估计，查看查看第一类错误区间是否包含该概率，若不包含在接受备择假设\n",
    "    3. 以上二者的本质上都是该概率应该在第一类错误区间端点内侧【双边均满足】"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f7b9f63e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x1280 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.stats import chi2\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = np.arange(-1,20,0.1)\n",
    "df = np.arange(0.5,10.5,0.5)\n",
    "fig = plt.figure(figsize=(12,16),dpi=80)\n",
    "fig.suptitle(r'pdf of $\\chi^2$ distribution')\n",
    "plt.subplots_adjust(hspace=0.2,wspace=0.25)\n",
    "for i in range(len(df)):\n",
    "    plt.subplot(4,5,i+1).plot(x, chi2.pdf(x,df[i]),label=r'$\\nu$=%.2f'%df[i])\n",
    "    plt.subplot(4,5,i+1).set_title(r'$\\nu$=%.2f'%df[i])\n",
    "    plt.legend()\n",
    "    plt.grid(alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "23dbd15d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x1280 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xx = np.arange(-1,25,0.1)\n",
    "\n",
    "fig = plt.figure(figsize=(12,16),dpi=80)\n",
    "fig.suptitle(r'cdf of $\\chi^2 distribution$')\n",
    "plt.subplots_adjust(hspace=0.4,wspace=0.25)\n",
    "for i in range(len(df)):\n",
    "    plt.subplot(4,5,i+1).plot(xx, chi2.cdf(xx,df[i]),label=r'$\\nu$=%.2f'%df[i])\n",
    "    plt.subplot(4,5,i+1).set_title(r'$\\nu$=%.2f'%df[i])\n",
    "    plt.legend()\n",
    "    plt.grid(alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a000c7f9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "280.391px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
